An Integer Local Search Method with Application to Capacitated Production Planning

Production planning is an important task in manufacturing systems.
We consider a real-world capacitated lot-sizing problem (CLSP) from
the process industry. Because the problem requires discrete lot-sizes,
domain-specific methods from the literature are not directly
applicable. We therefore approach the problem with WSAT(OIP), a new
domain-independent heuristic for integer optimization which
generalizes the Walksat algorithm. WSAT(OIP) performs stochastic tabu
search and operates on over-constrained integer programs. We
empirically compare WSAT(OIP) to a state-of-the-art mixed integer
programming branch-and-bound solver (Cplex 4.0) on real problem data.
We find that integer local search is considerably more robust than MIP
branch-and-bound in finding feasible solutions in limited time, and
branch-and-bound can only solve a sub-class of the CLSP with discrete
lot-sizes. With respect to production cost, both methods find
solutions of similar quality.